Introduction to Oracle Big Data Discovery
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Transcript of Introduction to Oracle Big Data Discovery
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Oracle Big Data DiscoveryCON9101 - Introduction to Oracle Big Data Discovery
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Enterprise Use of Hadoop Continues to Mature
3%
21%
More Hadoop
0%
20%
40%
60%
80%
Hadoop Workloads
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76%
Less Same More
2
0%
ETL Data Science Business
Analytics
Today Future
Only 3% say they will do less with Hadoop over
the next 12 months
While ETL rules Hadoop’s first phase, Business Analytics will be the focus of
Hadoop’s second phase
2015 Hadoop Maturity Survey, conducted by AtScale Inc.
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Not Easy to Get Analytic Value at Fast Enough Pace
80% effort typically
spent on evaluating
and preparing data
Data Uncertainty
• Not familiar and overwhelming
• Potential value not obvious
• Requires significant manipulation
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Tool Complexity
• Early Hadoop tools only for experts
• Existing BI tools not designed for Hadoop
• Emerging solutions lack broad capabilities
Overly dependent on
scarce and highly
skilled resources
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Requires a Fundamentally New Approach
A single intuitive and visual user interface, to...
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quickly transform
and enrich it to make
it better
unlock big data for
anyone to discover
and share new value
find and explore big
data to understand its
potential
find explore transform discover
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Oracle Big Data Discovery. The Visual Face of Hadoop
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find explore transform discover
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Find
• Access a rich, interactive catalog of all data in Hadoop
• Familiar search and guided navigation for ease of use
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ease of use
• See data set summaries, user annotation and recommendations
• Provision personal and enterprise data to Hadoop via self-service
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Explore
• Visualize all attributes by type
• Sort attributes by information potential
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• Assess attribute statistics, data quality and outliers
• Use scratch pad to uncover correlations between attributes
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• Intuitive, user driven data wrangling
• Extensive library of powerful data transformations and
Transform
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transformations and enrichments
• Preview results, undo, commit and replay transforms
• Test on sample data then apply to full data set in Hadoop
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• Join and blend data for deeper perspectives
• Compose project pages via drag and drop
Discover
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drop
• Use powerful search and guided navigation to ask questions
• See new patterns in rich, interactive data visualizations
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Oracle Big Data Discovery. Technical Innovation on Hadoop
Oracle Big Data Discovery Workloads
Hadoop Cluster(BDA or Commodity Hardware)
BDD node
name node
In-Memory Discovery Indexes• For keyword search, faceted navigation and analytics
• Indexes data and organizes as key value pairs
Web Studio• Catalog, explore, transform and discover UI’s• Self service data provisioning to Hadoop• Metadata configuration and administration
Hadoop 2.x
Other Hadoop Workloads
MapReduce
Spark
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data node
data node
data node
data node
name node
BDD Data Processing (Spark on YARN)• Profiling: catalog entry creation, data type &
language detection, schema configuration
• Sampling: dgraph (index) file creation
• Transforms: >150 data wrangling functions
shipped out-of-the-box
• Enrichments: location (geo), text (cleanup,
sentiment, entity, key-phrase, whitelist tagging)
Self-Service Provisioning & Data Transfer• Personal Data: Import from JDBC, CSV and XLS to HDFS
Indexes data and organizes as key value pairs
• In-memory, columnar, multi-core architectureHadoop 2.x
Filesystem(HDFS)
Workload Mgmt(YARN)
Metadata(HCatalog) Hive
Pig
Oracle Big Data SQL (BDA only)
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Oracle Big Data Discovery. The Visual Face of HadoopOracle Big Data Discovery. The Visual Face of Hadoop
www.oracle.com/bigdatadiscovery